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AWS releases open-source benchmark for AI agents on AWS

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AWS has announced a research preview of aws-bench, an open-source benchmark designed to measure the accuracy and efficiency of AI agents performing tasks on AWS infrastructure. This tool addresses the need for objective, reproducible performance measurement and failure diagnosis for AI researchers and model providers. It includes a public suite of test cases based on real AWS usage scenarios and offers a CLI for easy execution and scoring, available now on GitHub.

  • →AWS introduces aws-bench for AI agent benchmarking
  • →Benchmarking methodology and availability
  • →Enables performance tracking and improvement for AI agents on AWS
Features (1) ›
  • AWS introduces aws-bench for AI agent benchmarking

    aws-bench is an open-source benchmark released in research preview by AWS to measure the accuracy and efficiency of AI agents performing real-world AWS tasks. It provides a public suite of test cases derived from actual AWS usage patterns for investigation, troubleshooting, and infrastructure creation.

Enhancements (1) ›
  • Enables performance tracking and improvement for AI agents on AWS

    Researchers and model providers can leverage aws-bench to enhance foundation model performance on AWS tasks, refine agent harnesses, and monitor progress over time. The tool aims to provide an objective and reproducible method for evaluating AI agent capabilities within AWS.

Notes (1) ›
  • Benchmarking methodology and availability

    Each test case in aws-bench pairs natural-language queries with defined cloud resource states and ground-truth answers, enabling consistent and verifiable scoring of AI agents. The release includes a CLI tool for setting up testing environments, executing evaluations, and managing resource states, with the benchmark available on GitHub.

Read the original announcement →

https://aws.amazon.com/about-aws/whats-new/2026/07/aws-bench/

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